Information sharing via social networking systems (SNS) is a common practice among academics, as well as others, that brings substantial benefits. At the same time, privacy concerns are widespread ...among SNS users, which may tend to inhibit their maximising the benefit from using the systems. This paper investigates the proposition that SNS user attitudes and behaviour are affected by privacy concerns, and that the effects are subject to significant cultural factors. A broad assessment of the literature provides the context for the study. Working in the context of Saudi Arabia, we apply a mixed-methods approach beginning with in-depth interviews, exposing in detail a range of views and concerns about privacy and SNS use, also allowing us to identify three key factors that bear on SNS usage and users' concerns. Analysis of these factors in the light of the "theory of reasoned action" derives a structural model predicting several hypotheses relating the factors and users' attitudes and behaviour. We assess the model through development of a questionnaire, administered to a large pool of academic participants, that allows us to examine how the model responds in general, and via multigroup partial least squares analyses, differentially to gender and to culturally distinct (Arab vs. non-Arab) constituents of the participant group. Results show good support for the hypotheses and clear gender and culture effects. Picking up issues from the interviews, discussion focuses on users' views about SNS providers' privacy policies and their inadequacy regarding culturally specific ethical concerns. We argue that these views may reflect different regulatory environments in combination with other cultural factors.
Crowd management is crucial for countries and organizations as it can lead to severe consequences or serious safety concerns. Most of the existing research focus on addressing limited crowd ...management issues, namely crowd counting, density estimation, localization, and behavior monitoring. Furthermore, the generated incidents' alerts are mostly not interpretable and remediable. Therefore, there is no comprehensive solution that addresses all these issues. This research proposes a comprehensive intelligence-based crowd management framework that employs anomaly rules to monitor, predict, and detect crowd accidents and help in providing quick response. The suggested crowd intelligence framework addresses all crowd management issues. The use case chosen for this framework is the management of crowds of pilgrims in Umrah Holy event. The proposed framework is then implemented and evaluated with respect to efficiency, scalability, interpretability, remediability, and the number of false positive, true positive, and false negative alerts. In addition, the suggested framework is compared with other recent related work in terms of supporting crowd management issues. The design of the proposed framework and implementation are then fine-tuned in light of the evaluation results. The results and findings of this research can be extended to manage crowds at any event.
Forecasting crowd congestion is a critical aspect of crowd management, particularly in dynamic and densely populated areas, such as urban centers, events, or pilgrimage sites. In this paper, we ...proposed the first crowd congestion forecasting framework for the pilgrimage of Umrah. We addressed the crowd congestion forecasting problem by clustering the crowd flow trajectory in Masjid Al-Haram (Great Mosque) in the city of Makkah into six zones. The framework consists of two main components: 1) Ensemble forecasting model that aims at forecasting the crowd density of Masjid Al-Haram and its six zones, and 2) decision making algorithm that aims at keeping the crowd density at an acceptable level, and recommends updating the crowd flows when the forecasted crowd density exceeds the crowd density threshold. We built the ensemble learning model in three phases. In the first phase, we selected and evaluated different learning base models, including ARIMA, Sequence to Sequence (Seq2Seq) learning, M-1D-CNN-LSTM, and DeepSTN. In the second phase, the best three models, which performed well in the first phase, are selected to build the stacked ensemble model. The latter is validated using the walk-forward technique in the third phase. To evaluate the framework, we built a crowd dataset based on two temporal properties: 1) hourly context and 2) daily context. We evaluated the three phases of the ensemble forecasting model. In the first phase, DeepSTN performs the best by achieving a Mean Absolute Error (MAE) of 0.281. The results also indicate that DeepSTN is the best fit for five zones, and one variant of Seq2Seq, named Seq2Seq2b is the best fit for one zone under Mean Square Error (MSE) and Root Mean Squared Error (RMSE). Under MAE, DeepSTN and Seq2Seq2b, each of which is the best choice for three zones. In the second phase, the stacked ensemble achieves a MAE of 0.257. In the third phase, the stacked ensemble model is validated using the walk forward technique, which allows to reduce the MAE to 0.253. Although this framework focuses on Umrah, it can be customized for other use cases that involve crowd congestion forecasting.
The rapid development of different social media and content-sharing platforms has been largely exploited to spread misinformation and fake news that make people believing in harmful stories, which ...allow to influence public opinion, and could cause panic and chaos among population. Thus, fake news detection has become an important research topic, aiming at flagging a specific content as fake or legitimate. The fake news detection solutions can be divided into three main categories: content-based, social context-based, and knowledge-based approaches. In this paper, we propose a novel hybrid fake news detection system that combines linguistic and knowledge-based approaches and inherits their advantages, by employing two different sets of features: (1) linguistic features (i.e., title, number of words, reading ease, lexical diversity,and sentiment), and (2) a novel set of knowledge-based features, called fact-verification features that comprise three types of information namely, (i) reputation of the website where the news is published, (ii) coverage , i.e., number of sources that published the news, and (iii) fact-check , i.e., opinion of well-known fact-checking websites about the news, i.e., true or false. The proposed system only employs eight features, which is less than most of the state-of-the-art approaches. Also, the evaluation results on a fake news dataset show that the proposed system employing both types of features can reach an accuracy of 94.4%, which is better compared to that obtained from separately employing linguistic features (i.e., accuracy=89.4%) and fact-verification features (i.e., accuracy=81.2%).
Organizations are required to implement an information security management system (ISMS) for making a central cybersecurity framework, reducing costs, treating risks, and so on. Several ISMS ...standards have been issued and implemented locally and internationally. In Saudi Arabia, the most widely implemented international ISMS is ISO/IEC 27001. Currently, the Saudi National Cybersecurity Authority (NCA) issued a local framework called Essential Cybersecurity Controls (NCA-ECC). Therefore, many ISO/IEC 27001 certified organizations in Saudi Arabia are trying to convert from ISO/IEC 27001 to NCA-ECC or comply with both frameworks. Nevertheless, cybersecurity experts need to know which cybersecurity controls are already implemented, based on the ISO/IEC 27001, and which are not. This paper first measures the extent to which certified ISO/IEC 27001 Saudi organizations comply with the NCA-ECC. Second, it presents a framework for complying with the required unimplemented or partially implemented NCA-ECC controls. The framework can also help organization to be in compliance with both frameworks, if required. Three ISO/IEC 27001-certified Saudi public universities are selected as samples. The data is collected by interviewing the cybersecurity officers in the selected universities. This research shows that certified ISO/IEC 27001 organizations are approximately 64% in compliance with the NCA-ECC. The presented framework can help any ISO/IEC 27001 certified Saudi organization convert from ISO/IEC 27001 to NCA-ECC in a quick and cost-effective manner by considering only NCA-ECC nonconformities.
A number of countries are today implementing open government data (OGD) initiatives. Yet many of these initiatives are failing to attract the levels of continuous use they need to deliver an ...acceptable return on investment. This raises the obvious question of why this should be the case. To answer this question, it is important to understand the factors that most strongly influence user behaviour in OGD adoption. Qualitative data were used to identify the factors that play a key role in influencing the intention to engage with ODG. A quantitative approach was then used to evaluate the extent to which these factors drive/limit behaviour. The study's findings showed that there are four factors that play a significant role in intention to use OGD. It is also believed that the findings will be useful in helping policymakers in all jurisdictions formulate and implement strategies that successfully drive up continuous OGD engagement.
Information sharing via social networking systems (SNS) is a common practice among academics, as well as others, that brings substantial benefits. At the same time, privacy concerns are widespread ...among SNS users, which may tend to inhibit their maximising the benefit from using the systems. This paper investigates the proposition that SNS user attitudes and behaviour are affected by privacy concerns, and that the effects are subject to significant cultural factors. A broad assessment of the literature provides the context for the study. Working in the context of Saudi Arabia, we apply a mixed-methods approach beginning with in-depth interviews, exposing in detail a range of views and concerns about privacy and SNS use, also allowing us to identify three key factors that bear on SNS usage and users' concerns. Analysis of these factors in the light of the "theory of reasoned action" derives a structural model predicting several hypotheses relating the factors and users' attitudes and behaviour. We assess the model through development of a questionnaire, administered to a large pool of academic participants, that allows us to examine how the model responds in general, and via multigroup partial least squares analyses, differentially to gender and to culturally distinct (Arab vs. non-Arab) constituents of the participant group. Results show good support for the hypotheses and clear gender and culture effects. Picking up issues from the interviews, discussion focuses on users' views about SNS providers' privacy policies and their inadequacy regarding culturally specific ethical concerns. We argue that these views may reflect different regulatory environments in combination with other cultural factors.
Computer forensics and privacy protection fields are two conflicting directions in computer security. In the other words, computer forensics tools try to discover and extract digital evidences ...related to a specific crime, while privacy protection techniquesaim at protecting the data owner's privacy. As a result, finding a balance between these two fields is a serious challenge. Existing privacy-preserving computer forensics solutions consider all data owner's data as private and, as a result, they collect and encrypt the entire data. This increases the investigation cost in terms of time and resources. So, there is a need for having privacy levels for computer forensics so that only relevant data are collected and then only private relevant data are encrypted. This research paper proposes privacy levels for computer forensics. It starts with classifying forensic data, and analyzing all data access possibilities in computer forensics. Then, it defines several privacy levels based on the found access possibilities. The defined privacy levels lead to more efficient privacy-preserving computer forensics solution.
Privacy policies for computer forensics Halboob, Waleed; Mahmod, Ramlan; Udzir, Nur Izura ...
Computer fraud & security,
August 2015, 2015-08-00, Letnik:
2015, Številka:
8
Journal Article
Recenzirano
Privacy policies are required by most, if not all, existing privacy acts to make clear how private data are collected, used and disclosed. They are used as a guideline by the data collector to ...control its behaviour. They also help the data owner to know how the data will be maintained. Therefore, defining privacy policies for computer forensics is an important legal issue to make the investigation process more lawful in terms of privacy preservation.
However, as Waleed Halboob, Ramlan Mahmod, Nur Izura Udzir and Mohd Taufik Abdullah of the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, explain, current policies and processes are inadequate. They propose a number of policies that cover all computer forensics investigation steps – imaging, analysis and presentation.
PDF
